Skip to main content

Lorem ipsum generator.

Project description

Lorem ipsum generator.

In publishing and graphic design, lorem ipsum is a placeholder text commonly used to demonstrate the visual form of a document or a typeface without relying on meaningful content.

The lorem module provides a generic access to generating the lorem ipsum text from its very original text:

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

Usage of the lorem module is rather simple. Depending on your needs, the lorem module provides generation of words, sentences, and paragraphs.

Get Random Words

The lorem module provides two different ways for getting random words.

  1. word -- generate a list of random words

    word(count=1, func=None, args=[], kwargs={}) -> Iterable[str]
    
  2. get_word -- return random words

    get_word(count=1, sep=' ', func=None, args=[], kwargs={}) -> str
    

Get Random Sentences

The lorem module provides two different ways for getting random sentences.

  1. sentence -- generate a list of random sentences

    sentence(count=1, comma=(0, 2), word_range=(4, 8)) -> Iterable[str]
    
  2. get_sentence -- return random sentences

    get_sentence(count=1, comma=(0, 2), word_range=(4, 8), sep=' ') -> Union[str]
    

Get Random Paragraphs

The lorem module provides two different ways for getting random paragraphs.

  1. paragraph -- generate a list of random paragraphs

    paragraph(count=1, comma=(0, 2), word_range=(4, 8), sentence_range=(5, 10)) -> Iterable[str]
    
  2. get_paragraph -- return random paragraphs

    get_paragraph(count=1, comma=(0, 2), word_range=(4, 8), sentence_range=(5, 10), sep=os.linesep) -> Union[str]
    

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

python-lorem-1.3.0rc1.tar.gz (10.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

python_lorem-1.3.0rc1-py3-none-any.whl (9.1 kB view details)

Uploaded Python 3

File details

Details for the file python-lorem-1.3.0rc1.tar.gz.

File metadata

  • Download URL: python-lorem-1.3.0rc1.tar.gz
  • Upload date:
  • Size: 10.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.3

File hashes

Hashes for python-lorem-1.3.0rc1.tar.gz
Algorithm Hash digest
SHA256 2535d789548d1ace5e600d9d9e2b1d918aee2a920c247f579804df015150b245
MD5 599b6bc976249c3e77eaacd2b7481885
BLAKE2b-256 b7d3fa58e3aa667fdaebbdf10f0eebb49e0cf609eea1525b0f02a6d17d3e0dfc

See more details on using hashes here.

File details

Details for the file python_lorem-1.3.0rc1-py3-none-any.whl.

File metadata

File hashes

Hashes for python_lorem-1.3.0rc1-py3-none-any.whl
Algorithm Hash digest
SHA256 8758e24608a238d832fedf77cbaf3eacac64da0578b7af48fc85b32d4e7f48f6
MD5 bfbee8adcbf76df203bb9013af1167bb
BLAKE2b-256 1f2af211d6c47a822edb3b13406d0a4b4e8deaac80480acf9bbe954bd96b941e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page